Congratulations to Wei Li (an MPhil student supervised by Prof. Bei Yu) and co-authors (Yuxiao Qu, Gengjie Chen, Yuzhe Ma, Bei Yu) won the Best Paper Award at the 26th ACM/IEEE Asia and South Pacific Design Automation Conference (ASP-DAC 2021) for their paper “TreeNet: Deep Point Cloud Embedding for Routing Tree Construction”.
ASP-DAC 2021 is the twenty-sixth annual international conference on VLSI design automation in Asia and South Pacific region, one of the most active regions of design and fabrication of silicon chips in the world. The conference aims at providing the Asian and South Pacific CAD/DA and Design community with opportunities of presenting recent advances and with forums for future directions in technologies related to Electronic Design Automation (EDA).
Abstract：
In the routing tree construction, both wirelength (WL) and path-length (PL) are of importance. Among all methods, PD-II and SALT are the two most prominent ones. However, neither PD-II nor SALT always dominates the other one in terms of both WL and PL for all nets. In addition, estimating the best parameters for both algorithms is still an open problem. In this paper, they model the pins of a net as point cloud and formalize a set of special properties of such point cloud. Considering these properties, they propose a novel deep neural net architecture, TreeNet, to obtain the embedding of the point cloud. Based on the obtained cloud embedding, an adaptive workflow is designed for the routing tree construction. Experimental results show that the proposed TreeNet is superior to other mainstream models for the point cloud on classification tasks. Moreover, the proposed adaptive workflow for the routing tree construction outperforms SALT and PD-II in terms of both efficiency and effectiveness.
